{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cc6de67d",
   "metadata": {},
   "source": [
    "## 数据分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4507a01d",
   "metadata": {},
   "source": [
    "### 本文将对主要独角兽企业的投资机构，金融科技企业进行分析"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2342738d",
   "metadata": {},
   "source": [
    "#### 在全行业中，金融科技企业市值占比最高，其中蚂蚁金服功不可没，其市值突破万亿，不仅仅作为金融科技行业第一，也处于独角兽企业第一的位置，它位于环杭州湾大湾区，而杭州湾大湾区也受益于金融科技的红利，独角兽金融科技企业大都成立于2014到2016年，其中蚂蚁金服就成立于2014年，\n",
    "#### 在蚂蚁金服的投资机构背后，红衫资本的格外引人关注，他投资了57家独角兽企业，市值超过1万亿，距离他的下一名腾讯市值接近三倍\n",
    "#### 投资机构比较青睐于投资金融科技、媒体娱乐、共享经济领域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "f99a3888",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly as py\n",
    "import cufflinks as cf\n",
    "import pyecharts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "id": "cd9caf2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 206 entries, 0 to 205\n",
      "Data columns (total 11 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   排名            206 non-null    int64 \n",
      " 1   企业名称          206 non-null    object\n",
      " 2   Company Name  206 non-null    object\n",
      " 3   估值（亿人民币）      206 non-null    int64 \n",
      " 4   国家            206 non-null    object\n",
      " 5   城市            206 non-null    object\n",
      " 6   行业            206 non-null    object\n",
      " 7   掌门人/创始人       206 non-null    object\n",
      " 8   成立年份          206 non-null    int64 \n",
      " 9   部分投资机构        206 non-null    object\n",
      " 10  湾区            184 non-null    object\n",
      "dtypes: int64(3), object(8)\n",
      "memory usage: 17.8+ KB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>湾区</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>264</td>\n",
       "      <td>网易有道</td>\n",
       "      <td>Youdao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>周枫</td>\n",
       "      <td>2007</td>\n",
       "      <td>君联资本、慕华投资</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "3      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "4     11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "201  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "202  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "203  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "204  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "205  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构       湾区  \n",
       "0            春华资本、中投海外、红杉资本  环杭州湾大湾区  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投    渤海大湾区  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本    渤海大湾区  \n",
       "3       摩根士丹利、中银集团、国泰君安（香港）  环杭州湾大湾区  \n",
       "4               腾讯、华平投资、淡马锡   粤港澳大湾区  \n",
       "..                      ...      ...  \n",
       "201          高瓴资本、晨兴资本、软银中国    渤海大湾区  \n",
       "202               君联资本、慕华投资    渤海大湾区  \n",
       "203          华平投资、红杉资本、经纬中国    渤海大湾区  \n",
       "204          顺为资本、达晨创投、华平投资  环杭州湾大湾区  \n",
       "205                      腾讯    渤海大湾区  \n",
       "\n",
       "[206 rows x 11 columns]"
      ]
     },
     "execution_count": 224,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv (r'C:\\Users\\16019\\Desktop\\week13\\hurun_2019\\hurun.csv', encoding = \"utf8\", sep=\"\\t\").rename(columns={\"region\":\"湾区\"})\n",
    "df.info()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c39288",
   "metadata": {},
   "source": [
    "### 创始人拆分并统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "7a6469eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      井贤栋\n",
       "1      张一鸣\n",
       "2       程维\n",
       "3      计葵生\n",
       "4       顾敏\n",
       "      ... \n",
       "201    吴逸然\n",
       "202     周枫\n",
       "203     韩毅\n",
       "204     张翼\n",
       "205    姚劲波\n",
       "Name: 掌门人/创始人(拆), Length: 206, dtype: object"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['掌门人/创始人'].str.split(',', expand=True).stack().reset_index(level=1,drop=True).rename('掌门人/创始人(拆)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "c70a4ab1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
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       "      <th>序号</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>井贤栋</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>张一鸣</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>程维</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>计葵生</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "      <td>顾敏</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>吴逸然</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>264</td>\n",
       "      <td>网易有道</td>\n",
       "      <td>Youdao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>周枫</td>\n",
       "      <td>2007</td>\n",
       "      <td>君联资本、慕华投资</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>周枫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>韩毅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>张翼</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>姚劲波</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "3      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "4     11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "201  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "202  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "203  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "204  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "205  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构       湾区 掌门人/创始人(拆)  \n",
       "序号                                               \n",
       "0            春华资本、中投海外、红杉资本  环杭州湾大湾区        井贤栋  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投    渤海大湾区        张一鸣  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本    渤海大湾区         程维  \n",
       "3       摩根士丹利、中银集团、国泰君安（香港）  环杭州湾大湾区        计葵生  \n",
       "4               腾讯、华平投资、淡马锡   粤港澳大湾区         顾敏  \n",
       "..                      ...      ...        ...  \n",
       "201          高瓴资本、晨兴资本、软银中国    渤海大湾区        吴逸然  \n",
       "202               君联资本、慕华投资    渤海大湾区         周枫  \n",
       "203          华平投资、红杉资本、经纬中国    渤海大湾区         韩毅  \n",
       "204          顺为资本、达晨创投、华平投资  环杭州湾大湾区         张翼  \n",
       "205                      腾讯    渤海大湾区        姚劲波  \n",
       "\n",
       "[206 rows x 12 columns]"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index.name=\"序号\"\n",
    "df_创始人拆分 =pd.merge(df,\\\n",
    "                     df['掌门人/创始人'].str.split(',', expand=True).stack().reset_index(level=1,drop=True).rename('掌门人/创始人(拆)'),\\\n",
    "                     on=\"序号\")\n",
    "df_创始人拆分\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "447d805e",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业名称</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>掌门人/创始人(拆)</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "    <tr>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>崔晶晶</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
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       "      <td>70</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>杨正大</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 2 columns</p>\n",
       "</div>"
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       "            估值（亿人民币）  企业名称\n",
       "掌门人/创始人(拆)                \n",
       "井贤栋            10000     1\n",
       "张一鸣             5000     1\n",
       "程维              3600     1\n",
       "计葵生             2700     1\n",
       "顾敏              1500     1\n",
       "...              ...   ...\n",
       "江建飞               70     1\n",
       "崔晓波               70     1\n",
       "崔晶晶               70     1\n",
       "段毅                70     1\n",
       "杨正大               70     1\n",
       "\n",
       "[200 rows x 2 columns]"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_创始人拆分[[\"企业名称\",\"估值（亿人民币）\",\"掌门人/创始人(拆)\"]]\\\n",
    "                .groupby([\"掌门人/创始人(拆)\"])\\\n",
    "                .agg({\"估值（亿人民币）\":\"sum\",\"企业名称\":\"count\"})\\\n",
    "                .sort_values(\"估值（亿人民币）\",ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "d39db18e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_创始人拆分.head(20).to_html('创始人拆分.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "49fec295",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['井贤栋',\n",
       " '张一鸣',\n",
       " '程维',\n",
       " '计葵生',\n",
       " '顾敏',\n",
       " '童文红',\n",
       " '陈生强',\n",
       " '宿华',\n",
       " '汪滔',\n",
       " '詹克团，吴忌寒',\n",
       " '王振辉',\n",
       " '左晖',\n",
       " '杨浩涌',\n",
       " '高菁',\n",
       " '刘传军',\n",
       " '叶望春',\n",
       " '张近东',\n",
       " '王刚',\n",
       " '徐立',\n",
       " '陆正耀']"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df_创始人拆分.head(20)[\"掌门人/创始人\"]\n",
    "x1=list(x)\n",
    "x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "0cae9ee8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10000,\n",
       " 5000,\n",
       " 3600,\n",
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       " 1500,\n",
       " 1300,\n",
       " 1300,\n",
       " 1200,\n",
       " 1000,\n",
       " 800,\n",
       " 800,\n",
       " 600,\n",
       " 600,\n",
       " 600,\n",
       " 500,\n",
       " 500,\n",
       " 500,\n",
       " 400,\n",
       " 400,\n",
       " 400]"
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     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "y=df_创始人拆分.head(20)[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "y1"
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  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "51cd0fde",
   "metadata": {},
   "outputs": [
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       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u521b\\u59cb\\u4eba\\u62c6\\u5206(\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"slider\",\n",
       "        \"realtime\": true,\n",
       "        \"start\": 20,\n",
       "        \"end\": 80,\n",
       "        \"orient\": \"horizontal\",\n",
       "        \"zoomLock\": false,\n",
       "        \"filterMode\": \"filter\"\n",
       "    }\n",
       "};\n",
       "                chart_cee963b2e3584c0c90bae23cccdabffe.setOption(option_cee963b2e3584c0c90bae23cccdabffe);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b693cd60>"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l1=x1\n",
    "l2=y1\n",
    "bar = (\n",
    "    Bar()\n",
    "    .add_xaxis(l1)\n",
    "    .add_yaxis(\"创始人拆分(亿人民币)\", l2)\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"创始人拆分(\"),\n",
    "                     datazoom_opts=opts.DataZoomOpts(type_=\"slider\"))\n",
    ")\n",
    "bar.render_notebook()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "67439cca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\创始人拆分.html'"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('创始人拆分.html')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ee0c040",
   "metadata": {},
   "source": [
    "### 部分投资机构拆分并统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "da9ff21b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_部分投资机构拆分 = pd.merge(df,\\\n",
    "                            df['部分投资机构'].str.split('[,,、]', expand=True)\\\n",
    "                            .stack().reset_index(level=1, drop=True).rename('部分投资机构(拆)'),\\\n",
    "                            on=\"序号\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "id": "9f6c6fdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>湾区</th>\n",
       "      <th>部分投资机构(拆)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>春华资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>中投海外</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>海纳亚洲</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>经纬中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>顺为资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>达晨创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>华平投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>腾讯</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>597 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "203  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "204  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "204  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "204  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "205  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                  部分投资机构       湾区 部分投资机构(拆)  \n",
       "序号                                           \n",
       "0         春华资本、中投海外、红杉资本  环杭州湾大湾区      春华资本  \n",
       "0         春华资本、中投海外、红杉资本  环杭州湾大湾区      中投海外  \n",
       "0         春华资本、中投海外、红杉资本  环杭州湾大湾区      红杉资本  \n",
       "1    红杉资本、海纳亚洲、纪源资本、启明创投    渤海大湾区      红杉资本  \n",
       "1    红杉资本、海纳亚洲、纪源资本、启明创投    渤海大湾区      海纳亚洲  \n",
       "..                   ...      ...       ...  \n",
       "203       华平投资、红杉资本、经纬中国    渤海大湾区      经纬中国  \n",
       "204       顺为资本、达晨创投、华平投资  环杭州湾大湾区      顺为资本  \n",
       "204       顺为资本、达晨创投、华平投资  环杭州湾大湾区      达晨创投  \n",
       "204       顺为资本、达晨创投、华平投资  环杭州湾大湾区      华平投资  \n",
       "205                   腾讯    渤海大湾区        腾讯  \n",
       "\n",
       "[597 rows x 12 columns]"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_部分投资机构拆分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "c08ea525",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>城市</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>北京</th>\n",
       "      <td>84030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>杭州</th>\n",
       "      <td>39800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>上海</th>\n",
       "      <td>25570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>深圳</th>\n",
       "      <td>12790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>广州</th>\n",
       "      <td>3750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>南京</th>\n",
       "      <td>3610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵阳</th>\n",
       "      <td>2400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>天津</th>\n",
       "      <td>2100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成都</th>\n",
       "      <td>1070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>香港</th>\n",
       "      <td>940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>武汉</th>\n",
       "      <td>600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>青岛</th>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>重庆</th>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>无锡</th>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金华</th>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>台北</th>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>桐乡</th>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绍兴</th>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    估值（亿人民币）\n",
       "城市          \n",
       "北京     84030\n",
       "杭州     39800\n",
       "上海     25570\n",
       "深圳     12790\n",
       "广州      3750\n",
       "南京      3610\n",
       "贵阳      2400\n",
       "天津      2100\n",
       "成都      1070\n",
       "香港       940\n",
       "武汉       600\n",
       "青岛       300\n",
       "重庆       270\n",
       "无锡       210\n",
       "金华       210\n",
       "台北       140\n",
       "桐乡       140\n",
       "绍兴       100"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_部分投资机构拆分[['城市','部分投资机构(拆)','估值（亿人民币）']]\\\n",
    "                .groupby(['城市'])\\\n",
    "                .agg({'估值（亿人民币）':'sum'})\\\n",
    "                .sort_values('估值（亿人民币）',ascending=False)\n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "137cd0b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '北京',\n",
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       " '上海',\n",
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       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '香港',\n",
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       " '南京',\n",
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       " '北京',\n",
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       " '成都',\n",
       " '成都',\n",
       " '成都',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
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       " '广州',\n",
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       " '杭州',\n",
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       " '深圳',\n",
       " '深圳',\n",
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       " '杭州',\n",
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       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
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       " '北京',\n",
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       " '上海',\n",
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       " '杭州',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '杭州',\n",
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       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '南京',\n",
       " '南京',\n",
       " '南京',\n",
       " '香港',\n",
       " '香港',\n",
       " '香港',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '杭州',\n",
       " '天津',\n",
       " '天津',\n",
       " '天津',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '深圳',\n",
       " '青岛',\n",
       " '青岛',\n",
       " '青岛',\n",
       " '深圳',\n",
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       " '深圳',\n",
       " '深圳',\n",
       " '北京',\n",
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       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
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       " '深圳',\n",
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       " '杭州',\n",
       " '杭州',\n",
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       " '上海',\n",
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       " '成都',\n",
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       " '杭州',\n",
       " '杭州',\n",
       " '南京',\n",
       " '南京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
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       " '北京',\n",
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       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '南京',\n",
       " '南京',\n",
       " '南京',\n",
       " '桐乡',\n",
       " '桐乡',\n",
       " '无锡',\n",
       " '无锡',\n",
       " '无锡',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '广州',\n",
       " '广州',\n",
       " '南京',\n",
       " '南京',\n",
       " '南京',\n",
       " '重庆',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '成都',\n",
       " '成都',\n",
       " '成都',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '香港',\n",
       " '香港',\n",
       " '香港',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '金华',\n",
       " '金华',\n",
       " '金华',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '北京',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '北京',\n",
       " '北京',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '台北',\n",
       " '台北',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '杭州',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '广州',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '深圳',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '北京',\n",
       " '上海',\n",
       " '上海',\n",
       " '上海',\n",
       " '北京']"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df_部分投资机构拆分[\"城市\"]\n",
    "x1=list(x)\n",
    "x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "cdeb171b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10000,\n",
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      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y=df_部分投资机构拆分[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "y1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "88afeb9a",
   "metadata": {},
   "outputs": [
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       "    ],\n",
       "    \"yAxis\": [\n",
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       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e0d\\u540c\\u57ce\\u5e02\\u6295\\u8d44\\u673a\\u6784\\u7684\\u603b\\u4f30\\u503c\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"slider\",\n",
       "        \"realtime\": true,\n",
       "        \"start\": 20,\n",
       "        \"end\": 80,\n",
       "        \"orient\": \"horizontal\",\n",
       "        \"zoomLock\": false,\n",
       "        \"filterMode\": \"filter\"\n",
       "    }\n",
       "};\n",
       "                chart_3bde951a922b4685857140bfc5b035e1.setOption(option_3bde951a922b4685857140bfc5b035e1);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b6943d00>"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l1=x1\n",
    "l2=y1\n",
    "bar = (\n",
    "    Bar()\n",
    "    .add_xaxis(l1)\n",
    "    .add_yaxis(\"不同城市投资机构的总估值)\", l2)\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"不同城市投资机构的总估值\"),\n",
    "                     datazoom_opts=opts.DataZoomOpts(type_=\"slider\"))\n",
    ")\n",
    "bar.render_notebook()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "f9b0e322",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\不同城市投资机构的总估值.html'"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('不同城市投资机构的总估值.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "af653a7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u4e0d\\u540c\\u6295\\u8d44\\u673a\\u6784\\u7684\\u603b\\u4f30\\u503c\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1540,\n",
       "                1930,\n",
       "                2100,\n",
       "                2700,\n",
       "                2700,\n",
       "                2700,\n",
       "                2800,\n",
       "                2830,\n",
       "                2850,\n",
       "                2970,\n",
       "                5450,\n",
       "                5520,\n",
       "                5810,\n",
       "                6230,\n",
       "                7510,\n",
       "                10000,\n",
       "                11040,\n",
       "                11300,\n",
       "                11890,\n",
       "                30860\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"right\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"markPoint\": {\n",
       "                \"symbolSize\": 80,\n",
       "                \"label\": {\n",
       "                    \"show\": true,\n",
       "                    \"position\": \"inside\",\n",
       "                    \"color\": \"#fff\",\n",
       "                    \"margin\": 8\n",
       "                },\n",
       "                \"data\": [\n",
       "                    {\n",
       "                        \"type\": \"average\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"type\": \"max\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"type\": \"min\"\n",
       "                    }\n",
       "                ]\n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u4e0d\\u540c\\u6295\\u8d44\\u673a\\u6784\\u7684\\u603b\\u4f30\\u503c\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u4e0d\\u540c\\u6295\\u8d44\\u673a\\u6784\\u7684\\u603b\\u4f30\\u503c\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"\\u767e\\u5ea6\",\n",
       "                \"\\u987a\\u4e3a\\u8d44\\u672c\",\n",
       "                \"\\u771f\\u683c\\u57fa\\u91d1\",\n",
       "                \"\\u56fd\\u6cf0\\u541b\\u5b89\\uff08\\u9999\\u6e2f\\uff09\",\n",
       "                \"\\u6668\\u5174\\u8d44\\u672c\",\n",
       "                \"\\u4e2d\\u94f6\\u96c6\\u56e2\",\n",
       "                \"\\u6469\\u6839\\u58eb\\u4e39\\u5229\",\n",
       "                \"\\u9ad8\\u74f4\\u8d44\\u672c\",\n",
       "                \"\\u534e\\u5e73\\u6295\\u8d44\",\n",
       "                \"\\u6de1\\u9a6c\\u9521\",\n",
       "                \"IDG\",\n",
       "                \"\\u963f\\u91cc\\u5df4\\u5df4\",\n",
       "                \"\\u7ecf\\u7eac\\u4e2d\\u56fd\",\n",
       "                \"\\u6d77\\u7eb3\\u4e9a\\u6d32\",\n",
       "                \"\\u542f\\u660e\\u521b\\u6295\",\n",
       "                \"\\u4e2d\\u6295\\u6d77\\u5916\",\n",
       "                \"\\u7eaa\\u6e90\\u8d44\\u672c\",\n",
       "                \"\\u6625\\u534e\\u8d44\\u672c\",\n",
       "                \"\\u817e\\u8baf\",\n",
       "                \"\\u7ea2\\u6749\\u8d44\\u672c\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e0d\\u540c\\u6295\\u8d44\\u673a\\u6784\\u7684\\u603b\\u4f30\\u503c(\\u4ebf\\u4eba\\u6c11\\u5e01)\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_bf7541be190048a1b37696281c3ecf78.setOption(option_bf7541be190048a1b37696281c3ecf78);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b6648ac0>"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Bar\n",
    "x=df_投资数量.head(20)[\"投资机构\"]\n",
    "x1=list(x)\n",
    "x1.reverse()\n",
    "x1\n",
    "\n",
    "y=df_投资数量.head(20)[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "y1.reverse()\n",
    "y1\n",
    "\n",
    "x_vals1 = x1\n",
    "y_vals = y1\n",
    "bar = Bar().add_xaxis(x_vals1)      \n",
    "bar.add_yaxis('不同投资机构的总估值', y_vals, \n",
    "               markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_='average'),\n",
    "                                                 opts.MarkPointItem(type_='max'),\n",
    "                                                 opts.MarkPointItem(type_='min')], \n",
    "                                                symbol_size=80)\n",
    "              ) \n",
    "bar.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position='right'))\n",
    "bar.set_global_opts(title_opts=opts.TitleOpts(title='不同投资机构的总估值(亿人民币)'))\n",
    "bar.reversal_axis() #翻转XY轴，将柱状图转换为条形图\n",
    "bar.render_notebook()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "0a13a412",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\不同投资机构的总估值.html'"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('不同投资机构的总估值.html')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9308dfc2",
   "metadata": {},
   "source": [
    "### 独角兽企业数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "f0ba119b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业名称</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>行业</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>金融科技</th>\n",
       "      <td>52750</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>媒体和娱乐</th>\n",
       "      <td>30640</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>共享经济</th>\n",
       "      <td>21380</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>电子商务</th>\n",
       "      <td>13070</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>物流</th>\n",
       "      <td>12670</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>人工智能</th>\n",
       "      <td>7760</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>健康科技</th>\n",
       "      <td>6200</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新能源汽车</th>\n",
       "      <td>5490</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>软件与服务</th>\n",
       "      <td>4930</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>机器人</th>\n",
       "      <td>4500</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>教育科技</th>\n",
       "      <td>4170</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>区块链</th>\n",
       "      <td>3850</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>房地产科技</th>\n",
       "      <td>2780</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大数据</th>\n",
       "      <td>1820</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>消费品</th>\n",
       "      <td>1760</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>云计算</th>\n",
       "      <td>1340</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新零售</th>\n",
       "      <td>1000</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生命科学</th>\n",
       "      <td>810</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>网络安全</th>\n",
       "      <td>600</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>游戏</th>\n",
       "      <td>300</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新能源</th>\n",
       "      <td>210</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       估值（亿人民币）  企业名称\n",
       "行业                   \n",
       "金融科技      52750    64\n",
       "媒体和娱乐     30640    49\n",
       "共享经济      21380    24\n",
       "电子商务      13070    95\n",
       "物流        12670    51\n",
       "人工智能       7760    52\n",
       "健康科技       6200    34\n",
       "新能源汽车      5490    32\n",
       "软件与服务      4930    48\n",
       "机器人        4500    10\n",
       "教育科技       4170    35\n",
       "区块链        3850     8\n",
       "房地产科技      2780    18\n",
       "大数据        1820    23\n",
       "消费品        1760    11\n",
       "云计算        1340    14\n",
       "新零售        1000    12\n",
       "生命科学        810     8\n",
       "网络安全        600     3\n",
       "游戏          300     3\n",
       "新能源         210     3"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##  估值最多的行业\n",
    "df_部分投资机构拆分[['企业名称','估值（亿人民币）','行业']]\\\n",
    "                .groupby(['行业'])\\\n",
    "                .agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    "                .sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    "#                 .reset_index()\\"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "b1bebff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"73a6241557194b5cbcfdc69b37a892fb\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_73a6241557194b5cbcfdc69b37a892fb = echarts.init(\n",
       "                    document.getElementById('73a6241557194b5cbcfdc69b37a892fb'), 'white', {renderer: 'canvas'});\n",
       "                var option_73a6241557194b5cbcfdc69b37a892fb = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
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       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
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       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u4e0d\\u540c\\u884c\\u4e1a\\u7684\\u603b\\u4f30\\u503c\",\n",
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       "                \"\\u623f\\u5730\\u4ea7\\u79d1\\u6280\",\n",
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       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
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       "                \"\\u4eba\\u5de5\\u667a\\u80fd\",\n",
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       "                \"\\u5065\\u5eb7\\u79d1\\u6280\",\n",
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       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
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       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
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       "                \"\\u6d88\\u8d39\\u54c1\",\n",
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       "                \"\\u5927\\u6570\\u636e\",\n",
       "                \"\\u5927\\u6570\\u636e\",\n",
       "                \"\\u5927\\u6570\\u636e\",\n",
       "                \"\\u5065\\u5eb7\\u79d1\\u6280\",\n",
       "                \"\\u5065\\u5eb7\\u79d1\\u6280\",\n",
       "                \"\\u5065\\u5eb7\\u79d1\\u6280\",\n",
       "                \"\\u4e91\\u8ba1\\u7b97\",\n",
       "                \"\\u4e91\\u8ba1\\u7b97\",\n",
       "                \"\\u4e91\\u8ba1\\u7b97\",\n",
       "                \"\\u4e91\\u8ba1\\u7b97\",\n",
       "                \"\\u4e91\\u8ba1\\u7b97\",\n",
       "                \"\\u623f\\u5730\\u4ea7\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
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       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7269\\u6d41\",\n",
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       "                \"\\u7269\\u6d41\",\n",
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       "                \"\\u5a92\\u4f53\\u548c\\u5a31\\u4e50\",\n",
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       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u91d1\\u878d\\u79d1\\u6280\",\n",
       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
       "                \"\\u8f6f\\u4ef6\\u4e0e\\u670d\\u52a1\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u7269\\u6d41\",\n",
       "                \"\\u6559\\u80b2\\u79d1\\u6280\",\n",
       "                \"\\u6559\\u80b2\\u79d1\\u6280\",\n",
       "                \"\\u6559\\u80b2\\u79d1\\u6280\",\n",
       "                \"\\u7535\\u5b50\\u5546\\u52a1\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e0d\\u540c\\u884c\\u4e1a\\u7684\\u603b\\u4f30\\u503c(\\u4ebf\\u4eba\\u6c11\\u5e01))\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"slider\",\n",
       "        \"realtime\": true,\n",
       "        \"start\": 20,\n",
       "        \"end\": 80,\n",
       "        \"orient\": \"horizontal\",\n",
       "        \"zoomLock\": false,\n",
       "        \"filterMode\": \"filter\"\n",
       "    }\n",
       "};\n",
       "                chart_73a6241557194b5cbcfdc69b37a892fb.setOption(option_73a6241557194b5cbcfdc69b37a892fb);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b66488e0>"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df_部分投资机构拆分[\"行业\"]\n",
    "x1=list(x)\n",
    "\n",
    "y=df_部分投资机构拆分[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "\n",
    "\n",
    "l1=x1\n",
    "l2=y1\n",
    "bar = (\n",
    "    Bar()\n",
    "    .add_xaxis(l1)\n",
    "    .add_yaxis(\"不同行业的总估值\", l2)\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"不同行业的总估值(亿人民币))\"),\n",
    "                     datazoom_opts=opts.DataZoomOpts(type_=\"slider\"))\n",
    ")\n",
    "bar.render_notebook()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "440ff36d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\不同行业总估值.html'"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('不同行业总估值.html')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb9ded1d",
   "metadata": {},
   "source": [
    "### 金融科技企业"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "209a3db7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>序号</th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>湾区</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>京东数科</td>\n",
       "      <td>JD Digits</td>\n",
       "      <td>1300</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>陈生强</td>\n",
       "      <td>2013</td>\n",
       "      <td>红杉资本、嘉实投资、中国太平</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15</td>\n",
       "      <td>34</td>\n",
       "      <td>金融壹账通</td>\n",
       "      <td>OneConnect</td>\n",
       "      <td>500</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>叶望春</td>\n",
       "      <td>2015</td>\n",
       "      <td>IDG、思佰益</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>16</td>\n",
       "      <td>34</td>\n",
       "      <td>苏宁金服</td>\n",
       "      <td>Suning Finance</td>\n",
       "      <td>500</td>\n",
       "      <td>中国</td>\n",
       "      <td>南京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>张近东</td>\n",
       "      <td>2006</td>\n",
       "      <td>光大控股、深创投</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>31</td>\n",
       "      <td>84</td>\n",
       "      <td>银联商务</td>\n",
       "      <td>China UMS</td>\n",
       "      <td>200</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>田林</td>\n",
       "      <td>2002</td>\n",
       "      <td>光际资本、IDG</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>35</td>\n",
       "      <td>84</td>\n",
       "      <td>度小满金融</td>\n",
       "      <td>Du Xiaoman Financial</td>\n",
       "      <td>200</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>朱光</td>\n",
       "      <td>2018</td>\n",
       "      <td>TPG、凯雷投资，泰康集团、农银国际</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>65</td>\n",
       "      <td>138</td>\n",
       "      <td>PingPong</td>\n",
       "      <td>PingPong</td>\n",
       "      <td>150</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>陈宇</td>\n",
       "      <td>2015</td>\n",
       "      <td>广发信德、清华控股、Fidelity</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>111</td>\n",
       "      <td>264</td>\n",
       "      <td>百融金服</td>\n",
       "      <td>100credit</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>张韶峰</td>\n",
       "      <td>2014</td>\n",
       "      <td>中国国新、中金前海、红杉资本、IDG、高瓴资本</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>115</td>\n",
       "      <td>264</td>\n",
       "      <td>玖富</td>\n",
       "      <td>9fgroup</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>孙雷</td>\n",
       "      <td>2006</td>\n",
       "      <td>晨兴资本、DCM、SIG</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>116</td>\n",
       "      <td>264</td>\n",
       "      <td>空中云汇</td>\n",
       "      <td>Airwallex</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jack Zhang</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、红杉资本、DST、高瓴资本</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>117</td>\n",
       "      <td>264</td>\n",
       "      <td>岩心科技</td>\n",
       "      <td>Akulaku</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>李文博</td>\n",
       "      <td>2015</td>\n",
       "      <td>启明创投、蚂蚁金服</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>131</td>\n",
       "      <td>264</td>\n",
       "      <td>点融网</td>\n",
       "      <td>Dianrong</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>苏海德</td>\n",
       "      <td>2012</td>\n",
       "      <td>老虎环球基金、北极光创投、GIC</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>135</td>\n",
       "      <td>264</td>\n",
       "      <td>易生金服</td>\n",
       "      <td>Easy Life</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>刘江涛</td>\n",
       "      <td>2011</td>\n",
       "      <td>海航旅游、H-capital</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>163</td>\n",
       "      <td>264</td>\n",
       "      <td>连连数字</td>\n",
       "      <td>Lianlian</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>章征宇</td>\n",
       "      <td>2009</td>\n",
       "      <td>红杉资本、光大实业、赛伯乐</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>165</td>\n",
       "      <td>264</td>\n",
       "      <td>联易融</td>\n",
       "      <td>Linklogis</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>宋群</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、泛海投资、中信资本</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>180</td>\n",
       "      <td>264</td>\n",
       "      <td>人人贷</td>\n",
       "      <td>Renrendai</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>杨一夫</td>\n",
       "      <td>2010</td>\n",
       "      <td>挚信资本</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>182</td>\n",
       "      <td>264</td>\n",
       "      <td>水滴</td>\n",
       "      <td>Shuidi</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>沈鹏</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、创新工场、IDG、美团点评</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>190</td>\n",
       "      <td>264</td>\n",
       "      <td>挖财</td>\n",
       "      <td>Wacai</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>李治国</td>\n",
       "      <td>2009</td>\n",
       "      <td>新天域资本、光信资本、IDG、启明创投</td>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>191</td>\n",
       "      <td>264</td>\n",
       "      <td>我来贷</td>\n",
       "      <td>WeLab</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>谢飞</td>\n",
       "      <td>2014</td>\n",
       "      <td>阿里巴巴、淡马锡、红杉资本</td>\n",
       "      <td>粤港澳大湾区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>201</td>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "      <td>渤海大湾区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     序号   排名      企业名称          Company Name  估值（亿人民币）  国家  城市    行业  \\\n",
       "0     0    1      蚂蚁金服         Ant Financial     10000  中国  杭州  金融科技   \n",
       "1     3    6       陆金所                 Lufax      2700  中国  上海  金融科技   \n",
       "2     4   11      微众银行                WeBank      1500  中国  深圳  金融科技   \n",
       "3     6   12      京东数科             JD Digits      1300  中国  北京  金融科技   \n",
       "4    15   34     金融壹账通            OneConnect       500  中国  上海  金融科技   \n",
       "5    16   34      苏宁金服        Suning Finance       500  中国  南京  金融科技   \n",
       "6    31   84      银联商务             China UMS       200  中国  上海  金融科技   \n",
       "7    35   84     度小满金融  Du Xiaoman Financial       200  中国  北京  金融科技   \n",
       "8    65  138  PingPong              PingPong       150  中国  杭州  金融科技   \n",
       "9   111  264      百融金服             100credit        70  中国  北京  金融科技   \n",
       "10  115  264        玖富               9fgroup        70  中国  北京  金融科技   \n",
       "11  116  264      空中云汇             Airwallex        70  中国  香港  金融科技   \n",
       "12  117  264      岩心科技               Akulaku        70  中国  深圳  金融科技   \n",
       "13  131  264       点融网              Dianrong        70  中国  上海  金融科技   \n",
       "14  135  264      易生金服             Easy Life        70  中国  北京  金融科技   \n",
       "15  163  264      连连数字              Lianlian        70  中国  杭州  金融科技   \n",
       "16  165  264       联易融             Linklogis        70  中国  深圳  金融科技   \n",
       "17  180  264       人人贷             Renrendai        70  中国  北京  金融科技   \n",
       "18  182  264        水滴                Shuidi        70  中国  北京  金融科技   \n",
       "19  190  264        挖财                 Wacai        70  中国  杭州  金融科技   \n",
       "20  191  264       我来贷                 WeLab        70  中国  深圳  金融科技   \n",
       "21  201  264       有利网                 Yooli        70  中国  北京  金融科技   \n",
       "\n",
       "       掌门人/创始人  成立年份                   部分投资机构       湾区  \n",
       "0          井贤栋  2014           春华资本、中投海外、红杉资本  环杭州湾大湾区  \n",
       "1          计葵生  2011      摩根士丹利、中银集团、国泰君安（香港）  环杭州湾大湾区  \n",
       "2           顾敏  2014              腾讯、华平投资、淡马锡   粤港澳大湾区  \n",
       "3          陈生强  2013           红杉资本、嘉实投资、中国太平    渤海大湾区  \n",
       "4          叶望春  2015                  IDG、思佰益  环杭州湾大湾区  \n",
       "5          张近东  2006                 光大控股、深创投      NaN  \n",
       "6           田林  2002                 光际资本、IDG  环杭州湾大湾区  \n",
       "7           朱光  2018       TPG、凯雷投资，泰康集团、农银国际    渤海大湾区  \n",
       "8           陈宇  2015       广发信德、清华控股、Fidelity  环杭州湾大湾区  \n",
       "9          张韶峰  2014  中国国新、中金前海、红杉资本、IDG、高瓴资本    渤海大湾区  \n",
       "10          孙雷  2006             晨兴资本、DCM、SIG    渤海大湾区  \n",
       "11  Jack Zhang  2016         腾讯、红杉资本、DST、高瓴资本   粤港澳大湾区  \n",
       "12         李文博  2015                启明创投、蚂蚁金服   粤港澳大湾区  \n",
       "13         苏海德  2012         老虎环球基金、北极光创投、GIC  环杭州湾大湾区  \n",
       "14         刘江涛  2011           海航旅游、H-capital    渤海大湾区  \n",
       "15         章征宇  2009            红杉资本、光大实业、赛伯乐  环杭州湾大湾区  \n",
       "16          宋群  2016             腾讯、泛海投资、中信资本   粤港澳大湾区  \n",
       "17         杨一夫  2010                     挚信资本    渤海大湾区  \n",
       "18          沈鹏  2016         腾讯、创新工场、IDG、美团点评    渤海大湾区  \n",
       "19         李治国  2009      新天域资本、光信资本、IDG、启明创投  环杭州湾大湾区  \n",
       "20          谢飞  2014            阿里巴巴、淡马锡、红杉资本   粤港澳大湾区  \n",
       "21         吴逸然  2012           高瓴资本、晨兴资本、软银中国    渤海大湾区  "
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_金融科技企业=df[df['行业'].str.contains('金融科技',na=False)].reset_index()\n",
    "df_金融科技企业"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "f6bc12c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>湾区</th>\n",
       "      <th>行业</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>环杭州湾大湾区</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>13760</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>渤海大湾区</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>1920</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>粤港澳大湾区</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>1780</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        湾区    行业  估值（亿人民币）  企业数量\n",
       "0  环杭州湾大湾区  金融科技     13760     8\n",
       "1    渤海大湾区  金融科技      1920     8\n",
       "2   粤港澳大湾区  金融科技      1780     5"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_金融科技企业=df_金融科技企业[['企业名称','行业','估值（亿人民币）','湾区']]\\\n",
    "                .groupby(['湾区','行业'])\\\n",
    "                .agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    "                .sort_values('估值（亿人民币）',ascending=False).reset_index().rename(columns={\"企业名称\":\"企业数量\"})\n",
    "df_金融科技企业"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "707a0fdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_金融科技企业.to_html(\"湾区公司数量.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "id": "cd924d92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['粤港澳大湾区', '渤海大湾区', '环杭州湾大湾区']"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df_金融科技企业[\"湾区\"]\n",
    "x1=list(x)\n",
    "x1.reverse()\n",
    "x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "8dec7e1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1780, 1920, 13760]"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y=df_金融科技企业[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "y1.reverse()\n",
    "y1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "9cdb94b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"6a0b19154c964accbd791043a56c33c3\" style=\"width:1000px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_6a0b19154c964accbd791043a56c33c3 = echarts.init(\n",
       "                    document.getElementById('6a0b19154c964accbd791043a56c33c3'), 'white', {renderer: 'canvas'});\n",
       "                var option_6a0b19154c964accbd791043a56c33c3 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"funnel\",\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"\\u7ca4\\u6e2f\\u6fb3\\u5927\\u6e7e\\u533a\",\n",
       "                    \"value\": 1780\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6e24\\u6d77\\u5927\\u6e7e\\u533a\",\n",
       "                    \"value\": 1920\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u73af\\u676d\\u5dde\\u6e7e\\u5927\\u6e7e\\u533a\",\n",
       "                    \"value\": 13760\n",
       "                }\n",
       "            ],\n",
       "            \"sort\": \"descending\",\n",
       "            \"gap\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"inside\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"itemStyle\": {\n",
       "                \"borderColor\": \"#fff\",\n",
       "                \"borderWidth\": 1\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u6e24\\u6d77\\u5927\\u6e7e\\u533a\",\n",
       "                \"\\u73af\\u676d\\u5dde\\u6e7e\\u5927\\u6e7e\\u533a\",\n",
       "                \"\\u7ca4\\u6e2f\\u6fb3\\u5927\\u6e7e\\u533a\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u7ca4\\u6e2f\\u6fb3\\u5927\\u6e7e\\u533a\": true,\n",
       "                \"\\u6e24\\u6d77\\u5927\\u6e7e\\u533a\": true,\n",
       "                \"\\u73af\\u676d\\u5dde\\u6e7e\\u5927\\u6e7e\\u533a\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e09\\u5927\\u6e7e\\u533a\\u7684\\u4f30\\u503c\",\n",
       "            \"subtext\": \"\\u4f30\\u503c\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_6a0b19154c964accbd791043a56c33c3.setOption(option_6a0b19154c964accbd791043a56c33c3);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b6ced0a0>"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Funnel\n",
    "\n",
    "\n",
    "data = [[x1[i], y1[i]] for i in range(len(x1))]\n",
    "\n",
    "(\n",
    "    Funnel(init_opts=opts.InitOpts(width=\"1000px\", height=\"500px\"))\n",
    "    .add(\n",
    "        series_name=\"\",\n",
    "        data_pair=data,\n",
    "        gap=2,\n",
    "#         tooltip_opts=opts.TooltipOpts(trigger=\"item\", formatter=\"{a} <br/>{b} : {c}%\"),\n",
    "        label_opts=opts.LabelOpts(is_show=True, position=\"inside\"),\n",
    "        itemstyle_opts=opts.ItemStyleOpts(border_color=\"#fff\", border_width=1),\n",
    "    )\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"三大湾区的估值\", subtitle=\"估值\"))\n",
    "#     .render(\"funnel_chart.html\")\n",
    "   .render_notebook()\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "e7ce5d92",
   "metadata": {
    "code_folding": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\三大湾区估值.html'"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('三大湾区估值.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "f5c26b57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>成立年份</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2010</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2009</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2006</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    成立年份  企业数量\n",
       "0   2018     1\n",
       "1   2016     3\n",
       "2   2015     3\n",
       "3   2014     4\n",
       "4   2013     1\n",
       "5   2012     2\n",
       "6   2011     2\n",
       "7   2010     1\n",
       "8   2009     2\n",
       "9   2006     2\n",
       "10  2002     1"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_金融科技企业年份=df_金融科技企业[['企业名称','成立年份','行业']]\\\n",
    "                .groupby(['成立年份'])\\\n",
    "                .agg({'企业名称':'count'})\\\n",
    "                .sort_values(['成立年份'],ascending=False)\\\n",
    "                .reset_index().rename(columns={'部分投资机构(拆)':\"投资机构\",\"企业名称\":\"企业数量\"})\n",
    "df_金融科技企业年份"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "id": "736b1e04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"900ebcea691948969914b5abfa01dd6d\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_900ebcea691948969914b5abfa01dd6d = echarts.init(\n",
       "                    document.getElementById('900ebcea691948969914b5abfa01dd6d'), 'white', {renderer: 'canvas'});\n",
       "                var option_900ebcea691948969914b5abfa01dd6d = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u4e0d\\u540c\\u5e74\\u4efd\\u72ec\\u91d1\\u878d\\u79d1\\u6280\\u4f01\\u4e1a\\u6210\\u7acb\\u6570\\u91cf\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1,\n",
       "                3,\n",
       "                3,\n",
       "                4,\n",
       "                1,\n",
       "                2,\n",
       "                2,\n",
       "                1,\n",
       "                2,\n",
       "                2,\n",
       "                1\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u4e0d\\u540c\\u5e74\\u4efd\\u72ec\\u91d1\\u878d\\u79d1\\u6280\\u4f01\\u4e1a\\u6210\\u7acb\\u6570\\u91cf\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u4e0d\\u540c\\u5e74\\u4efd\\u72ec\\u91d1\\u878d\\u79d1\\u6280\\u4f01\\u4e1a\\u6210\\u7acb\\u6570\\u91cf\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                2018,\n",
       "                2016,\n",
       "                2015,\n",
       "                2014,\n",
       "                2013,\n",
       "                2012,\n",
       "                2011,\n",
       "                2010,\n",
       "                2009,\n",
       "                2006,\n",
       "                2002\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u4e0d\\u540c\\u5e74\\u4efd\\u91d1\\u878d\\u79d1\\u6280\\u4f01\\u4e1a\\u6210\\u7acb\\u6570\\u91cf(\\u4ebf\\u4eba\\u6c11\\u5e01)\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"slider\",\n",
       "        \"realtime\": true,\n",
       "        \"start\": 20,\n",
       "        \"end\": 80,\n",
       "        \"orient\": \"horizontal\",\n",
       "        \"zoomLock\": false,\n",
       "        \"filterMode\": \"filter\"\n",
       "    }\n",
       "};\n",
       "                chart_900ebcea691948969914b5abfa01dd6d.setOption(option_900ebcea691948969914b5abfa01dd6d);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b678d850>"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Bar\n",
    "x=df_金融科技企业年份[\"成立年份\"]\n",
    "x1=list(x)\n",
    "y=df_金融科技企业年份[\"企业数量\"]\n",
    "y1=list(y)\n",
    "#柱形图\n",
    "l1=x1\n",
    "l2=y1\n",
    "bar = (\n",
    "    Bar()\n",
    "    .add_xaxis(l1)\n",
    "    .add_yaxis(\"不同年份独金融科技企业成立数量\", l2)\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"不同年份金融科技企业成立数量(亿人民币)\"),\n",
    "                     datazoom_opts=opts.DataZoomOpts(type_=\"slider\"))\n",
    ")\n",
    "bar.render_notebook()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "2dd7444a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\不同行业公司数量图.html'"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('不同行业公司数量图.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "0a3678ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>投资机构</th>\n",
       "      <th>企业数量</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>红杉资本</td>\n",
       "      <td>57</td>\n",
       "      <td>30860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>腾讯</td>\n",
       "      <td>33</td>\n",
       "      <td>11890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>春华资本</td>\n",
       "      <td>2</td>\n",
       "      <td>11300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>纪源资本</td>\n",
       "      <td>13</td>\n",
       "      <td>11040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>中投海外</td>\n",
       "      <td>1</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>华平资本</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>众信旅游</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>点亮资本</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>滴滴</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>国新</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     投资机构  企业数量  估值（亿人民币）\n",
       "0    红杉资本    57     30860\n",
       "1      腾讯    33     11890\n",
       "2    春华资本     2     11300\n",
       "3    纪源资本    13     11040\n",
       "4    中投海外     1     10000\n",
       "..    ...   ...       ...\n",
       "235  华平资本     1        70\n",
       "236  众信旅游     1        70\n",
       "237  点亮资本     1        70\n",
       "238    滴滴     1        70\n",
       "239    国新     1        70\n",
       "\n",
       "[240 rows x 3 columns]"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_投资数量=df_部分投资机构拆分[['企业名称','部分投资机构(拆)','估值（亿人民币）']]\\\n",
    "                .groupby(['部分投资机构(拆)'])\\\n",
    "                .agg({'企业名称':'count','估值（亿人民币）':'sum'})\\\n",
    "                .sort_values('估值（亿人民币）',ascending=False).reset_index().rename(columns={\"企业名称\":\"企业数量\",\"部分投资机构(拆)\":\"投资机构\"})\n",
    "df_投资数量"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba76ab32",
   "metadata": {},
   "source": [
    "### 投资机构估值对比"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "98a5305c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "                    document.getElementById('9aaef2609cb64ea5837a8d9aca8171fc'), 'white', {renderer: 'canvas'});\n",
       "                var option_9aaef2609cb64ea5837a8d9aca8171fc = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
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       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u6295\\u8d44\\u673a\\u6784\\u7684\\u4f30\\u503c\",\n",
       "            \"legendHoverLink\": true,\n",
       "            \"data\": [\n",
       "                1540,\n",
       "                1930,\n",
       "                2100,\n",
       "                2700,\n",
       "                2700,\n",
       "                2700,\n",
       "                2800,\n",
       "                2830,\n",
       "                2850,\n",
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       "                30860\n",
       "            ],\n",
       "            \"showBackground\": false,\n",
       "            \"barMinHeight\": 0,\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"barGap\": \"30%\",\n",
       "            \"large\": false,\n",
       "            \"largeThreshold\": 400,\n",
       "            \"seriesLayoutBy\": \"column\",\n",
       "            \"datasetIndex\": 0,\n",
       "            \"clip\": true,\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 2,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"right\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"markPoint\": {\n",
       "                \"symbolSize\": 80,\n",
       "                \"label\": {\n",
       "                    \"show\": true,\n",
       "                    \"position\": \"inside\",\n",
       "                    \"color\": \"#fff\",\n",
       "                    \"margin\": 8\n",
       "                },\n",
       "                \"data\": [\n",
       "                    {\n",
       "                        \"type\": \"average\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"type\": \"max\"\n",
       "                    },\n",
       "                    {\n",
       "                        \"type\": \"min\"\n",
       "                    }\n",
       "                ]\n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u6295\\u8d44\\u673a\\u6784\\u7684\\u4f30\\u503c\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u6295\\u8d44\\u673a\\u6784\\u7684\\u4f30\\u503c\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
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       "            \"nameGap\": 15,\n",
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       "                \"\\u6668\\u5174\\u8d44\\u672c\",\n",
       "                \"\\u4e2d\\u94f6\\u96c6\\u56e2\",\n",
       "                \"\\u6469\\u6839\\u58eb\\u4e39\\u5229\",\n",
       "                \"\\u9ad8\\u74f4\\u8d44\\u672c\",\n",
       "                \"\\u534e\\u5e73\\u6295\\u8d44\",\n",
       "                \"\\u6de1\\u9a6c\\u9521\",\n",
       "                \"IDG\",\n",
       "                \"\\u963f\\u91cc\\u5df4\\u5df4\",\n",
       "                \"\\u7ecf\\u7eac\\u4e2d\\u56fd\",\n",
       "                \"\\u6d77\\u7eb3\\u4e9a\\u6d32\",\n",
       "                \"\\u542f\\u660e\\u521b\\u6295\",\n",
       "                \"\\u4e2d\\u6295\\u6d77\\u5916\",\n",
       "                \"\\u7eaa\\u6e90\\u8d44\\u672c\",\n",
       "                \"\\u6625\\u534e\\u8d44\\u672c\",\n",
       "                \"\\u817e\\u8baf\",\n",
       "                \"\\u7ea2\\u6749\\u8d44\\u672c\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u6295\\u8d44\\u673a\\u6784\\u4f30\\u503c\\u5bf9\\u6bd4(\\u4ebf\\u4eba\\u6c11\\u5e01)\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_9aaef2609cb64ea5837a8d9aca8171fc.setOption(option_9aaef2609cb64ea5837a8d9aca8171fc);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x1d9b678deb0>"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Bar\n",
    "x=df_投资数量.head(20)[\"投资机构\"]\n",
    "x1=list(x)\n",
    "x1.reverse()\n",
    "x1\n",
    "\n",
    "y=df_投资数量.head(20)[\"估值（亿人民币）\"]\n",
    "y1=list(y)\n",
    "y1.reverse()\n",
    "y1\n",
    "\n",
    "x_vals1 = x1\n",
    "y_vals = y1\n",
    "bar = Bar().add_xaxis(x_vals1)      \n",
    "bar.add_yaxis('投资机构的估值', y_vals, \n",
    "               markpoint_opts=opts.MarkPointOpts(data=[opts.MarkPointItem(type_='average'),\n",
    "                                                 opts.MarkPointItem(type_='max'),\n",
    "                                                 opts.MarkPointItem(type_='min')], \n",
    "                                                symbol_size=80)\n",
    "              ) \n",
    "bar.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position='right'))\n",
    "bar.set_global_opts(title_opts=opts.TitleOpts(title='投资机构估值对比(亿人民币)'))\n",
    "bar.reversal_axis() #翻转XY轴，将柱状图转换为条形图\n",
    "bar.render_notebook()\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "515208b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\16019\\\\投资机构估值对比.html'"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bar.render('投资机构估值对比.html') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f325319d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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